Table 26 Context-specific deployment recommendations.

From: Novel metaheuristic optimized latent diffusion framework for automated oral disease detection in public health screening

Clinical context

Recommended synthetic ratio (95% CI)

Prevalence weighting strategy

Expected performance range (95% CI)

Key considerations

Confidence level

Risk assessment score

Population screening

50–75% (45–80%)

Natural prevalence weighted

84–89% accuracy (82–91%)

Balance sensitivity/specificity

High

3/10 (low risk)

Specialized clinics

75% (70–80%)

Hybrid balanced-weighted

91–96% accuracy (89–97%)

Maintain rare pathology detection

Very High

2/10 (very low risk)

Emergency settings

50% (40–60%)

Cost-sensitive learning

78–85% accuracy (75–87%)

Minimize false positives

Moderate

5/10 (moderate risk)

Research applications

75% (70–80%)

Artificially balanced

94–97% accuracy (93–98%)

Maximize overall performance

Very High

1/10 (minimal risk)

International deployment

60–70% (55–75%)

Population-specific weighting

82–88% accuracy (79–90%)

Account for prevalence variations

Moderate

4/10 (low-moderate risk)

Mobile screening

50–60% (45–65%)

Robust focal loss

79–86% accuracy (76–88%)

Handle extreme class imbalance

Moderate

5/10 (moderate risk)